基于RBF-PSO算法的浮筏隔振系统性能优化及轻量化设计

Performance optimization and lightweight design of floating raft vibration isolation system based on RBF-PSO algorithm

  • 摘要:
    目的 为了解决工程中浮筏隔振系统轻量化设计过程工作量大、迭代周期长的问题,提出一种基于RBF-PSO多目标优化算法的轻量化设计方法。
    方法 以板架式浮筏隔振系统为研究对象,基于ANSYS APDL建立有限元模型并分析其隔振性能和抗冲击性能。通过试验测试浮筏的隔振性能,并与数值仿真结果进行对比,验证数值仿真结果的准确性;采用完全有限差分法,对浮筏隔振系统进行参数灵敏度分析,通过灵敏度分析结果选择设计变量,并基于RBF-PSO多目标优化算法对浮筏进行轻量化设计。
    结果 研究结果表明:轻量化设计后,筏架质量为63.03 kg,相较原筏架减重31.92%。与此同时,浮筏隔振系统的隔振性能提升了2.48 dB,设备的抗冲击性能也有所提升。RBF-PSO多目标优化算法优化值与数值仿真计算值误差小于1%。
    结论 RBF-PSO多目标优化算法可有效应用于浮筏隔振系统的轻量化设计中。

     

    Abstract:
    Objective To address the challenges of heavy workload and long iterative cycles in the lightweight design of floating raft vibration isolation system in engineering applications, this study proposes a lightweight design method based on RBF-PSO multi-objective optimization algorithm.
    Method  Taking the plate-frame floating raft vibration isolation system as the research object, a finite element model was established using ANSYS APDL. The vibration isolation performance and impact resistance were evaluated through numerical simulation. Experimental tests were conducted to assess the vibration isolation performance of the floating raft. The accuracy of the numerical simulation was validated by comparing it with the experimental results. A full finite difference method was employed to analyze the parameter sensitivity of the floating raft vibration isolation system. Appropriate design variables were selected based on the sensitivity analysis. The lightweight design of the floating raft vibration isolation system was carried out using the RBF-PSO multi-objective optimization algorithm.
    Results  The results show that after optimization, the mass of the raft is 63.03 kg. Compared with the original design, the weight of the lightweight raft is reduced by 31.92%. The vibration isolation performance of the floating raft system improves by 2.48 dB. The impact resistance of the equipment is also improved. The discrepancy between the optimized result obtained by the RBF-PSO algorithm and the numerical simulation calculation is less than 1%.
    Conclusion  Therefore, the RBF-PSO multi-objective optimization algorithm can be effectively applied to the lightweight design of the floating raft vibration isolation system.

     

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